Interference mitigation is a key challenge in improving the capacity of future wireless networks. In a densely deployed and interference-limited network, an effective way to mitigate interference is through power control. The successful implementation of power control is, however, also dependent on its algorithmic complexity, the hardware limitations of the wireless front-end, and especially the ability to integrate power control with system-level operations such as scheduling.
The use of power control for interference mitigation is of particular interest for wireless backhaul networks, which are deployed as a means to increase the network throughput for areas with high data traffic demand.
Interference mitigation is a particular consideration in the development of next-generation wireless backhaul products for compact base-stations, and Non Line of Sight (NLOS)-type backhaul networks, for example. NLOS backhaul technology provides a cost-effective approach for increasing the cell site capacity of PicoCell and MicroCell deployments. In a system of this type, a cellular network may comprise several PicoCells, each covering a relatively small area, as a means to increase the network capacity for areas with dense data traffic. The users within each PicoCell are served by their own PicoCell base-station, also called access modules (AM). The AMs are co-located with the remote backhaul modules (RBM) of the backhaul network. Each RBM is connected to a hub via wireless backhaul radio links. These radio links provide an alternative to expensive optical fiber links. Each hub serves multiple RBMs. The hubs are responsible for the transmission strategies and radio resource management for the different RBMs. Unlike the classical relay problem, the backhaul architecture assumes that the wireless backhaul links and the access links operate at different frequencies. From a backhaul design perspective, the interest is therefore in mitigating the interhub interference, thereby maximizing the aggregate data capacity of the RBMs and the backhaul network.
Typically, conventional wireless backhaul networks operate using a maximum power transmission strategy. However, it is desirable to be able to optimally adjust the power level of the radio transmitters with the goal of reducing undesirable interference. This power control problem has been extensively studied in the literature.
In general, power allocation is inherently coupled with scheduling. Thus, the optimization of the overall system performance requires a joint power control and scheduling. Existing efforts in the literature often involve either an exhaustive search, for small networks, or local iterative optimization of scheduling and power control, for which convergence and complexity may be issues for practical implementation. An iterative approach to joint power control and scheduling is disclosed, for example, in [1] the above referenced, related co-pending U.S. patent application Ser. No. 13/463,478, entitled “Interference Mitigation with Scheduling and Dynamic Power Spectrum Allocation for Wireless Networks” by Dahrouj et al., and in [2] PCT patent publication No. WO/2011/037319, published Mar. 31, 2011, by T. Kwon et al., entitled “Method and Device for User Scheduling and Managing Transmit Power in a Communication System”.
Other references that discuss scheduling and power control include: [3] S. G. Kiani and D. Gesbert, entitled “Optimal and Distributed Scheduling for Multicell Capacity Maximization” IEEE Trans. Wireless Commun., Vol. 7, No. 1, pp. 288-297, January 2008”; [4] L. Venturino, N. Prasad, and X. Wang, entitled “Coordinated Scheduling and Power Allocation In Downlink Multicell OFDMA Networks,” IEEE Trans. Veh. Technol., Vol. 6, No. 58, pp. 2835-2848, July 2009; and [5] A. L. Stolyar and H. Viswanathan, entitled “Self-Organizing Dynamic Fractional Frequency Reuse For Best-Effort Traffic Through Distributed Intercell Coordination,” in INFOCOM, April 2009.)
However, in practice, scheduling may happen on a different time scale than power control, thus, iteration between the power control and scheduling are not necessarily practical.
Thus, there is a need for alternative systems and methods for power control, and in particular, practically feasible methods for managing interference through power control, which provide low computational complexity and fast convergence.